Industrial Networks of the Future Across the Edge-to-Cloud Continuum

Dear Colleagues,

Modern industrial networks are undergoing a profound transformation driven by the convergence of digitalization, automation, and connectivity. The rise of Industry 4.0, the Industrial Internet of Things (IIoT), Cyber–Physical Systems (CPS), and intelligent edge-cloud integration is pushing traditional industrial communication paradigms to evolve into highly adaptable, software-defined infrastructures. These infrastructures must meet diverse and stringent requirements such as ultra-low latency, real-time responsiveness, high reliability, energy efficiency, and security.

The adoption of 5G/6G technologies, Time-Sensitive Networking (TSN), network slicing, and AI-driven automation is further accelerating this evolution. Industrial networks now span heterogeneous environments, ranging from resource-constrained edge and fog computing nodes to powerful cloud backends. This complexity demands new strategies for network design, orchestration, performance optimization, and security, all while supporting mission-critical applications in industrial applications such as manufacturing, logistics, etc.

This Special Issue will showcase cutting-edge research, novel architectures, and innovative solutions that advance the design, analysis, implementation, and evaluation of next-generation industrial networks. We invite contributions that address the unique challenges of industrial networking across the cloud-to-edge continuum, including real-time performance, determinism, resilience, and sustainability.

We particularly encourage submissions that undertake the following:

• Combine software-defined networking, network function virtualization, and edge-cloud orchestration for industrial applications;
• Address challenges in heterogeneous industrial environments with diverse communication and computational needs;
• Propose solutions for stringent Quality of Service (QoS) requirements (latency, reliability, throughput, energy efficiency);
• Introduce AI/ML-driven methods for adaptive control, optimization, and management in industrial networks;
• Present real-world deployments, use cases, and experimental evaluations.

Potential topics include but are not limited to the following areas:

1. Network Softwarization and Orchestration for Industrial Systems

• Software-Defined Networking (SDN) and Network Function Virtualization (NFV) in industrial settings;
• Orchestration-driven deployment of network services across heterogeneous industrial nodes;
• Service chaining, dynamic provisioning, in-network computing, and distributed orchestration for mission-critical applications.

2. Heterogeneous Compute Environments and Industrial IoT

• Architecture and performance modeling of cloud, fog, edge, and mobile edge computing (MEC) in industrial networks;
• Efficient resource placement, task offloading, and migration strategies for constrained devices;
• Integration of legacy systems with modern industrial communication platforms;
• Social IoT (human-centric IoT overlays, crowd-sourced edge nodes);
• Digital twin networks.

3. Quality of Service (QoS) and Resource Management

• Deterministic networking and Time-Sensitive Networking (TSN) in industrial applications;
• Real-time resource provisioning, energy-efficient scheduling, and multi-objective optimization;
• Low-latency communication and reliability enhancement for cyber-physical systems;
• Key Value Indicators (KVIs) and Ethical Networking (fairness, transparency, KPI/KVI trade-offs).

4. Performance Modeling, Simulation and Measurement

• Quantitative modeling and evaluation of industrial communication systems;
• Simulation frameworks for Industry 4.0 scenarios;
• Real-world testbeds, measurement campaigns, and benchmarking of industrial networks.

5. AI/ML-Driven Industrial Network Optimization

• Predictive maintenance, anomaly detection, and adaptive control using AI/ML techniques;
• Federated learning, edge intelligence, and distributed AI for industrial applications;
• AI-powered resource management and decision-making in networked industrial environments;
• AI for Network ( AI4NE ): data-driven control, intent prediction, and self-optimization;
• Network for AI ( NE4AI ): network architectures optimized for large-scale training/inference.

6. Security, Reliability and Resilience in Industrial Networks

• Security-by-design approaches for industrial networks and CPS;
• Cybersecurity, anomaly detection, intrusion prevention, and resilience against attacks;
• Fault tolerance, self-healing networks, and reliability mechanisms in software-defined industrial systems.

7. Emerging Domains and Vertical Applications

• Open RAN, private 5G/6G networks, and network slicing for industrial use cases;
• Smart factories, smart grids, smart transportation, and autonomous systems;
• Manufacturing, energy, logistics, and other Industry 4.0 applications empowered by advanced industrial networks;
• Green computing and sustainable networking (carbon-aware scheduling, renewable-powered edge, life-cycle assessment).

8. Localization, Navigation and Context Awareness

• High-accuracy localization and navigation techniques for industrial environments (e.g., factories, logistics, autonomous systems);
• 5G/6G-based positioning, ultra-wideband (UWB), visible light communication (VLC), and hybrid indoor/outdoor localization solutions;
• Context-aware services leveraging positioning, sensing, and mobility information for enhanced automation, safety, and efficiency.

This Special Issue is partially supported by the European Union under the Italian National Recovery and Resilience Plan (NRPP) of Next Generation EU (NGEU), partnership on "Telecommunications of the Future" (PE00000001—program "RESTART").

Dr. Lorenzo Mucchi
Dr. Laura Carnevali
Dr. Stefano Caputo
Guest Editors

Dr. Leonardo Scommegna
Guest Editor Assistant

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• network services
• industrial IoT
• software-defined networking (SDN)
• network function virtualization (NFV)
• quality of service (QoS)
• AI for network (AI4NE)
• network for AI (NE4AI)
• federated learning
• edge intelligence
• 5G/6G networks
• localization and navigation techniques